code: def _alignment(
      inter_mat,
      n_clusters,
      second_idx,
      result_mat_aligned,
      offset=OFFSET_FACTOR,
  ):
      index_mapping = np.zeros([n_clusters, 2])
      index_mapping[:, 0] = list(range(0, n_clusters))
  
      while np.sum(inter_mat) > (-1 * n_clusters * n_clusters):
          max_i, max_j = np.unravel_index(
              inter_mat.argmax(), inter_mat.shape
          )
          index_mapping[max_i, 1] = max_j
          inter_mat[max_i, :] = -1
          inter_mat[:, max_j] = -1
  
          # print('component 1 cluser', max_i, '==', 'component 2 cluser', max_j)
          result_mat_aligned[
              np.where(result_mat_aligned[:, second_idx] == max_j),
              second_idx,
          ] = (
              max_i + offset
          )
      return index_mapping
  
file_path: combo/combo/models/cluster_comb.py
imports: import numpy
  from sklearn.utils import check_array
  from sklearn.utils.validation import check_is_fitted
  from numpy.testing import assert_equal
  from pyod.utils.utility import check_parameter
  from .base import BaseAggregator
  from .score_comb import majority_vote
label_desc: Use image node_id 3 for calling a global function with example usage: _alignment(inter_mat, n_clusters, second_idx, result_mat_aligned, offset) and returns: index_mapping